Example submissions

The following submissions are provided as examples of how a submission can be constructed for each category. There are many ways to describe impact, so feel free to depart from these examples!

Technician: orienting fruit flies

Drosophila melanogaster is one of developmental biology’s unsung heroes: the humble fruit fly that annoys us all by hanging around the fruit bowl over summer has also been the model organism of choice of 10 Nobel Laureates. Flies have enabled major breakthroughs in our understanding of hereditary, mutation, circadian rhythms, immunity and odour reception, not to mention all the other research that hasn’t (yet) been awarded a Nobel Prize. 

One of the ways this little creature is used is to look in-situ at genes and proteins of interest in any given tissue. A major bottleneck in many experimental workflows in labs around the world is finding a correctly oriented Drosophila embryo on a microscope slide. This happens by pure chance; some will have their ventral (or belly) side facing up, others will have their dorsal (or back) side facing up, and every other possible angle in between. What if there is a way to position these embryos before we transfer them to the slide? That would mean every embryo is now useful and less time is wasted scanning manually over the slide to find the perfect one. This also frees up more time on the heavily booked confocal microscope in the core facility.

With the help of the university workshop, I invented a 3D printed device that allows the researcher to first orient the embryo using a very basic bright-field microscope, repeating this step for 20 embryos, and then using a heptane glue, transfer them to the microscope slide. 

I have shared the instructions for making or 3D printing the device with my department and mentioned it to my network and it’s now making a huge difference to lots of researchers’ work. It’s not a publishable finding as such but it’s definitely a worthy addition to any Drosophilist’s toolkit. 

Citizen Science: the Great Garden Spider Hunt 

The number and diversity of spiders is thought to be declining in the UK, but we are currently unsure of the reasons behind this change, and whether certain species are particularly affected.  Unlike other common garden species, e.g. birds, spiders are not typically celebrated by the public and the levels of spider identification is generally low. In this ambitious citizen science project researchers worked with community gardening and nature groups to co-develop Spider Identification training material to help volunteers identify spider types, along with supplementary material that explains the vital, but often overlooked, role that the different spider types play in maintaining a healthy garden ecosystem. 

In the second part of this project, the developed training and promotion materials were used in a large citizen science study in which gardeners were encouraged to log spider sightings over a 4 week period in Summer 2019.  Over 100 volunteers logged more than 400 sightings of garden spiders, with 5 different spider types identified.   Many volunteers also uploaded photographs and commented on the habitat, behaviour and beauty of the spiders in their garden.  Project evaluation was done through a follow up survey which despite having a relatively low response rate (15%), did reveal high levels of project satisfaction with 75% saying they would like to participate again.  One respondent wrote that involvement in the project  “lead to a newfound appreciation of the garden spiders and the wonders of nature”.

Grimpact: the “oops” and unintended consequences of economic modelling for COVID-19

Although hailed as “the simulations driving the world’s response to COVID-19” [1] and a vital tool in the predicting and planning of human behaviour, the use of economic modelling in the formation of policy decisions aimed to control the spread of COVID-19 infections.

Behavioural modelling at Imperial college was focused on bringing down infection, hospitalisation and death rates (succeeded) but had follow on political and economic consequences that were beyond the capabilities of the original epidemiology modelling to predict.  The follow-on effects, social political and economic, contrast the public benefits and impact of this body of research and, as outlined below, demonstrate a foreseeable, but unintended Grimpact.

[1]: https://www.nature.com/articles/d41586-020-01003-6

Impact: Positive effect on: policy, health, NHS workload

Grimpact: Negative effect on: economics, politics, society

Characteristics of grimpact central to this case

1 Contagion

Hooking onto the PAnon conspiracy theorists, and the misuse of data to fuel the development of anti-lockdown protests and political movements.

Drove the through of a binary decision between- boosting the economy versus saving lives.

2 Accountability/blame

Beyond the control of the original academics – applying a tool 

Reputational damage to Neil Ferguson, and diminishing the public-trust associated with following the government directions associated with lockdown.  This led to an unfortunate rise in COVID-19 cases, hospitalisations and associated deaths.

3 Violation of normal impact

Irresponsible interactions between research and stakeholders

4 Questions of research misconduct:

No evidence of research misconduct directly attributable to this body of research can be found.  However, there are an increasing number of COVID-19 research, including competing behavioural models, that are bypassing scholarly peer review as an academic governance tool.

Standards: Readme Citation Format

In 2019, Peabody et al published the Readme Citation Format (RCF) Version 1.2.3. RCF is a human- and machine- readable format for the readme citation files. These files provide citation metadata for the readme files that accompany research software.

Why was RCF needed? Well, you might think that a standard format for citing the readme files that accompany software is overkill. But it isn’t. Because before RCF there was no standardized, machine- and human- readable format for citing the readme files that accompany research software, only standardized, machine- and human- readable formats for CITATION files (see the excellent Citation File Format, or CFF). The goal of RCF is to address that clear gap by providing an all-purpose citation format (similar to BibTeX, RIS, or CFF) for readme files. As a result, RCF promotes attribution and credit for documenting software, and the documentation of research software in particular, by prompting or nudging users to cite the readme files that appear in software documentation, and by creating an ever more granular standardised ecology for software documentation citation.

Since its first inception in 2018, RCF has sought and received input from across the research software development community, and in its present form aims to provide a compromise between the ideal state of software documentation citation, i.e., perfect all the time everywhere, and the state of the practice, i.e., few people having ever really had the need to cite research software documentation.

RCF is published on GitHub under a Creative Commons Attribution 4.0 International License, with information at https://readme-citation-format.github.io/, and a citable version of the specification on Zenodo doi.org/10.0000/zenodo.1234567. The RCF enjoys a lively issue tracker https://github.com/readme-citation-format/readme-citation-format/issues that is indicative of the (somewhat surprising) level of community activity consolidating around the concept and practical utility of a readme citation format.